Cardiac arrest is widely-understood to be a substantial public health problem and a leading cause of death in most areas of the world. Each year in the U.S. and Canada, approximately 350,000 people suffer a cardiac arrest and receive attempted resuscitation. Accordingly, the medical community has long sought ways to more successfully treat cardiac arrest victims through CPR and application of defibrillation shocks to rapidly restore a normal heart rhythm to persons experiencing this type of event. AEDs were first developed decades ago to help treat incidents of cardiac arrest. Since their creation, AEDs have become prevalent in public locales such as offices, shopping centers, stadiums, and other areas of high pedestrian traffic. AEDs empower citizens to provide medical help during cardiac emergencies in public places where help was previously unavailable in the crucial early stages of a cardiac event.
Fully automated external defibrillators capable of accurately detecting ventricular arrhythmia and non-shockable supraventricular arrhythmia, such as those described in U.S. Pat. No. 5,474,574 to Payne et al., have been developed to treat unattended patients. These devices treat victims suffering from ventricular arrhythmias and have high sensitivity and specificity in detecting shockable arrhythmias in real-time. Further, AEDs have been developed to serve as diagnostic monitoring devices that can automatically provide therapy in hospital settings, as exhibited in U.S. Pat. No. 6,658,290 to Lin et al.
Despite advances in AED technology, many current AEDs are not fully functional in implementing the current medically suggested methods of integrated CPR and AED use. Most of the AEDs available today attempt to classify ventricular rhythms and distinguish between shockable ventricular rhythms and all other rhythms that are non-shockable. This detection and analysis of ventricular rhythms provides some real-time analysis of ECG waveforms. However, the functionality, accuracy and speed of a particular AED heavily depends on the algorithms and hardware utilized for analysis of ECG waveforms. In many implementations, the algorithms used in AEDs depend on heart rate calculations and a variety of morphology features derived from ECG waveforms, like ECG waveform factor and irregularity as disclosed in U.S. Pat. No. 5,474,574 to Payne et al. and U.S. Pat. No. 6,480,734 to Zhang et al. Further, in order to provide sufficient processing capability, current AEDs commonly embed the algorithms and control logic into microcontrollers.
As advances have taken place in the field of AEDs, there have been significant medical advancements in the understanding of human physiology and how it relates to medical care as well. These advancements in medical research have lead to the development of new protocols and standard operating procedures in dealing with incidents of physical trauma. For example, in public access protocols for defibrillation, recent guidelines have emphasized the need for the use of both CPR and AEDs and suggested an inclusive approach involving defibrillation integrated with CPR.
Along with its advantages, integrated use of CPR with defibrillation can, however, negatively impact the operation of an AED as chest compressions and relaxations are known to introduce significant motion artifacts in an ECG recording. During and after CPR, where a rescuer is instructed to apply chest compressions and relaxations at a prescribed rate of approximately 100 cycles per minute, the ability to obtain clean signal data from the patient can be challenging.
In addition to the difficulty of obtaining a clean ECG signal, the importance of doing this quickly has recently been highlighted as the current AHA Guidelines emphasize the importance of minimizing interruptions between CPR and defibrillation. The guidelines state, “[d]efibrillation outcome is improved if interruptions (for rhythm assessment, defibrillation, or advanced care) in chest compressions are kept to a minimum”, and “[m]inimizing the interval between stopping chest compressions and delivering a shock (ie, minimizing the preshock pause) improves the chances of shock success and patient survival.” See Circulation 2010, 122: S678, S641.
Some past AEDs implement an algorithm that requires an extended period of clean ECG signal data during a rescue to classify a sensed ventricular rhythm as shockable. Some prior art disclosures requiring a clean signal also discuss carrying out an initial assessment of ECG when CPR is ongoing, before relying on a temporary stoppage in CPR to acquire and perform an ECG analysis. Moreover, much of the recent scholarship in this area involves using tools which enable the entire analysis of ECG to take place while CPR is ongoing such that little or no stoppage of CPR is required. Accordingly, numerous techniques for identifying and filtering CPR artifacts for the purpose of ECG signal analysis have been proposed. However, many of these methods and analysis techniques have limitations or raise concerns related to providing appropriate care, especially in view of the newest AHA guidelines.
Accordingly, improved methods and apparatus for quickly assessing shockable cardiac rhythms which minimize any time periods between CPR and delivery of a defibrillation shock by an AED are desired.